In order to predict interactions between proteins and chemicals, the methods, such as docking analysis, for modeling the three-dimensional structures of such proteins and chemicals to calculate binding energy have been mainly studied. Many commercially available software programs have been developed (H. J. Bohm, The computer program LUDI: A new method for the de novo design of enzyme inhibitors, J. Comp. Aided. Mol. Des., Vol. 6, pp. 61-78, 1992; Y. Z. Chen and C. Y. Ung, Prediction of potential toxicity and side effect protein targets of a small molecule by a ligand-protein inverse docking approach, J. Mol. Graph. Mod., Vol. 20, pp. 199-218, 2001; Y. Z. Chen and D. G. Zhi, Ligand-protein inverse docking and its potential use in computer search of putative protein targets of a small molecule, Proteins, Vol. 43, pp. 217-226, 2001; Y. Z. Chen and C. Y. Ung, Computer automated prediction of putative therapeutic and toxicity protein targets of bioactive compounds from chinese medical plants, Am. J. Chin. Med., Vol. 30, pp. 139-154, 2002; Y. Z. Chen, Z. R. Li, and C. Y. Ung, Computational method for drug target search and application in drug discovery, J. Theor. Comp. Chem., Vol. 1, pp. 213-224, 2002; R. L. Desjarlais, R. P. Sheridan an G. L. Seibel, J. S. Dixon, I. D. Kuntz, and R. Venkataraghavan, Using shape complementarity as an initial screen in designing ligands for a receptor-binding site of known three-dimensional structure, J. Med. Chem., Vol. 31, pp. 722-729, 1988; T. E. Ferrin, G. S. Couch, C. C. Huang, E. F. Pellersen, and R. Langridge, An affordable approach to interactive desk-top molecular modeling, J. Mol. Graphics, Vol. 9; J. Goodford, A computational procedure for determining energetically favorable binding sites on biologically important macromolecules, J. Med. Chem., Vol. 28, pp. 849-857, 1985; G. Jones, P. WIllett, R. C. Glen, A. R. Leach, and R. Taylor, Development and calidation of a genetic algorithm for flexible dicking, J. Mol. Biol., Vol. 267, pp. 727-748, 1997; A. R. Leach and I. D. Kuntz, Conformational analysis of flexible ligands in macromolecular receptors sites, J. Comput. Chem., Vol. 13, pp. 730-748, 1992; A. Miranker and M. Karplus, Functionality maps of binding sites: A multicopy simultaneous search method, Proteins, Vol. 11, pp. 29-34, 1991; A. Miranker and M. Karplus, An automated method for dynamic ligand design, Proteins, Vol. 23, pp. 472-490, 1995; M. Y. Mizutani, N. Tomioka, and A. Itai, Rational automatic search method for stable docking models of protein and ligand, J. Mol. Biol., Vol. 243, pp. 310-326, 1994; C. M. Oshiro, I. D. Kuntz, and J. S. Dixon, Flexible ligand docking using a genetic algorithm, J. Comp. Aided Mol. Des., Vol. 9, pp. 113-130, 1995; C. M. Oshiro and I. D. Kuntz, Characterization of receptors with a new negative image: Use in molecular docking and lead optimization, Proteins, Vol. 30, pp. 321-336, 1998; S. H. Rostein, M. A. Murcko, and A. GenStar, A method for de novo drug design, J. Comp. Aided Mol. Des., Vol. 7, pp. 23-43, 1993; B. K. Shoichet, D. L. Bodian, and I. D. Kuntz, Molecular docking using shape descriptors, J. Comput. Chem., Vol. 13, pp. 380-397, 1992; and M. Zacharias, B. A. Luty, M. E. Davis, and J. A. McCammon, Combined conformational search and finite-difference poisson-boltazmann approach for flexible docking, J. Mol. Biol., Vol. 238, pp. 455-465, 1994). These methods are based on binding energy and therefore are highly reliable.